This disclosure relates generally to the field of image capture, and more particularly, to image capture devices with the ability to perform adaptive white balance correction using a switchable white reference.
The advent of portable integrated computing devices has caused a widespread proliferation of cameras and video devices. These integrated computing devices commonly take the form of smartphones or tablets and typically include general purpose computers, cameras, sophisticated user interfaces including touch sensitive screens, and wireless communications abilities through Wi-Fi, LTE, HSDPA and other cell-based or wireless technologies. The widespread proliferation of these integrated devices provides opportunities to use the devices' capabilities to perform tasks that would otherwise require dedicated hardware and software. For example, as noted above, integrated devices such as smartphones and tablets typically have two or more embedded cameras. These cameras generally amount to lens/camera hardware modules that may be controlled through the general purpose computer using firmware and/or software (e.g., “Apps”) and a user interface including the touch-screen fixed buttons and touchless control such as voice control.
The integration of cameras into communication devices such as smartphones and tablets has enabled people to share and view images and videos in ways never before possible. It is now very popular to acquire and immediately share photos with other people, either by sending the photos via text message, SMS, or email, or by uploading the photos to an Internet-based service, such as a social networking site or a photo sharing site.
Most portable integrated computing devices also incorporate at least one display screen to exchange information with users. Images may be captured by one or more cameras integrated with the device and displayed on the device's display screen, along with other content. During daily usage, users may experience numerous different ambient lighting conditions. The human eye and brain automatically adapt to the ambient lighting environment and process what is seen to be “color correct.” However, electronic devices are still largely agnostic to ambient lighting condition changes, which can cause problems that users can perceive.
One common problem relates to the fact that white balance is partially taken care of by the camera when images are captured, but the correction process is not perfect, and recorded images can often be tinted. In such cases, the recorded image does not accurately represent what the user actually perceived at the moment the image was captured. Thus, an object may be perceived by the user as perfectly “white” at the moment of image capture, but recorded by the camera as cyan-tinted.
A second problem relates to the fact that, other than reflective displays that utilize natural ambient lighting as the light source, all electronic devices utilize some type of internal light source. As a result, the images displayed on screen are often rendered agnostic of the ambient lighting conditions. Thus, the device's screen may have a correct physical white point, i.e., the emitted spectrum is supposed to produce correct white, however, if the user has been adapted to the particular lighting conditions in the ambient environment, the colors on the device's screen may not appear to be rendered correctly to the user. For example, in an ambient environment that has red-deficient lighting conditions, the device's screen may appear particularly reddish to the user.
Many studies have been conducted attempting to determine methods to allow automatic white balancing on cameras and post-processing of the images. A typical white balancing algorithm involves determining which part of image is “true white” and adjusting the remainder of the image based on the determined “true white” portion of the image. Typical choices of “true white” may be a shiny highlight spot on an object caused by specular reflection or large areas of objects that are recorded by the image sensor as having a color that is close to white.
However, there are limitations on how much a camera can correct the white balance of an image based on the captured images. The white balance correction process relies on the objects in the image providing enough relevant color information for the software to find a “true white.” Often, professional photographers shoot at a standard white reference first before taking photos of the targets in order to get an accurate white balance. As for the displays on consumer electronic devices, little has been done to satisfactorily correct the problem of adaptive white balance correction.